Employers today typically provide employees with numerous corporate electronic devices to perform their job duties. For example, an employer may provide an employee with a laptop, smartphone, and access badge. Recent advancements in information technology (“IT”) infrastructure have made it possible for employers to capture how employees use these devices, i.e., their “digital profile”. Additionally, organizations typically provide employees with computers that run applications for monitoring employee activities. For example, an employer may compile records of when an employee logs into or out of his or her workstation, when and where an employee remotely logs into or out of the corporate VPN network, when and how often an employee sends e-mails, and the times and locations the employee uses his or her security badges to access a physical location.
Additionally, employers may have alternate methods of monitoring or logging employee activities. For example, employers may perform biometric authentication in order to allow employees to access resources, such as physical areas, systems, or devices.
Though the data recorded from an employee's digital devices captures the use of the device, the data may also be used to determine employee activities and evaluate employee productivity. However, businesses typically find it difficult to analyze the data from each source independently, because the data can occasionally be ambiguous, and therefore an unreliable indicator of employee activity or productivity. For example, using badge swipe data to calculate employee attendance suffers from multiple ambiguities. Badge swipes do not account for employees working remotely or employees hold building doors open for each other, or broken or malfunctioning badge readers. Additionally, computing activity cannot be determined solely based on login activity to an office computing system, as employees are frequently provided with remote access capabilities.
Further, businesses typically find it difficult to aggregate the data from the different data sources for performing advanced employee productivity analysis. Because the digital profile data originates from disparate sources and devices, the digital profile data is typically captured and maintained in different structures. In some cases, the data has no structure at all. For example, records of security badge use, web traffic, anti-virus logs, and firewall logs are typically maintained as textual audit logs created in different formats. Thus, businesses find it difficult to aggregate data from different sources because the multiple data sources are typically maintained in different structures, or lack structure altogether.
Furthermore, even when aggregated, without an effective analysis framework, the collective data is of little use. While businesses have used technology to enhance employee efficiency, no solutions are available that measure efficiency based on device use and develop a plan for reconfiguration of resources based on the measurement. Additional problems exist that may be remedied by embodiments of the invention.